Chiara Aliberti
Automatic detection of new phishing domains using machine learning.
Rel. Marco Mellia. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
Abstract
Phishing is an online attack that tries to deceive its victims into revealing sensitive information, such as credentials or credit card details. The user is usually attracted by email (whaling, spear phishing, clone phishing) to malicious webpages that mimic the content of known legitimate websites. Over the years, phishing detection has become very relevant, mostly because of the fast-paced nature of the attack and the ever-growing scale of phishing campaigns, with the majority of phishing websites being alive for less than 24 hours and thousands of new phishing domains registered every day. This trend underlines the importance of lowering the window of vulnerability that occurs from the launch online to the detection of the malicious nature of the website.
This thesis work was carried out at the IT company Ermes Cyber Security to tackle this issue, attempting to identify phishing campaigns in their early phases, by starting the detection process from newly registered public-key certificates
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